Study on empathy, individual resilience, and training of speech-language pathology students using structural equation modeling

Introduction In Latin America, considerable variability has been observed in the distribution of empathy levels between sexes, as well as across different years of study and specialties among undergraduate students from various professions. This variability remains insufficiently explained. This study aims to predict empathy based on the resilience observed in Colombian speech therapy students. Methods A descriptive cross-sectional design was employed. The sample consisted of 217 speech therapy students, representing 94% of the population. Instruments used included the Jefferson Empathy Scale (Health Professions Student version) and the Individual Resilience Trait Scale. The sample underwent a multivariate outlier analysis using Mahalanobis distances. Descriptive analyses of univariate and multivariate normality (Mardia’s test) were conducted. Means, standard deviations, skewness, and kurtosis were calculated for each dimension of the constructs. For the empathy scale, a confirmatory factor analysis (CFA) was conducted using the robust maximum likelihood estimator (MLR). For the resilience scale, the weighted least squares estimator was applied. The cut-off points for the goodness-of-fit indices were CFI > 0.90, TLI > 0.90, RMSEA < 0.08, and SRMR < 0.10. Omega and alpha coefficients were calculated. The explanatory model was tested using Structural Equation Modeling. Analyses were performed with SPSS 27 and R (R Studio interface), employing the lavaan package version 0.6–17, psych version 2.4.1, semTools version 0.5–6, and MVN version 5.9. Results The perspective-taking dimension of empathy was significantly predicted by the ecological dimension (positively) and the adaptation dimension (negatively) of resilience. The other dimensions did not show predictive capacity. Conclusion This study concludes that resilience partially predicts empathy in the population studied. Therefore, resilience could be considered an attribute to incorporate into teaching-learning processes aimed at increasing empathy levels. The scope and implications of these findings are discussed.

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Publication Details

Journal
Frontiers in Education
Published
2025-11-13
DOI
https://doi.org/10.3389/feduc.2025.1677602
Citations
1
Primary Topic
Empathy and Medical Education
Type
article
Field-Weighted Citation Impact
1.47

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article

Study on empathy, individual resilience, and training of speech-language pathology students using structural equation modeling

José Gamarra‐Moncayo, Victor Patricio Díaz Narváez, Pilar Andrea Guzmán Sánchez, Yeniffer Mendez-Hurtado
1 citations
Frontiers in Education
Empathy and Medical Education
1.47
article

Study on empathy, individual resilience, and training of speech-language pathology students using structural equation modeling

José Gamarra‐Moncayo, Victor Patricio Díaz Narváez, Pilar Andrea Guzmán Sánchez, Yeniffer Mendez-Hurtado
article en
1 citations

Abstract

Introduction In Latin America, considerable variability has been observed in the distribution of empathy levels between sexes, as well as across different years of study and specialties among undergraduate students from various professions. This variability remains insufficiently explained. This study aims to predict empathy based on the resilience observed in Colombian speech therapy students. Methods A descriptive cross-sectional design was employed. The sample consisted of 217 speech therapy students, representing 94% of the population. Instruments used included the Jefferson Empathy Scale (Health Professions Student version) and the Individual Resilience Trait Scale. The sample underwent a multivariate outlier analysis using Mahalanobis distances. Descriptive analyses of univariate and multivariate normality (Mardia’s test) were conducted. Means, standard deviations, skewness, and kurtosis were calculated for each dimension of the constructs. For the empathy scale, a confirmatory factor analysis (CFA) was conducted using the robust maximum likelihood estimator (MLR). For the resilience scale, the weighted least squares estimator was applied. The cut-off points for the goodness-of-fit indices were CFI > 0.90, TLI > 0.90, RMSEA < 0.08, and SRMR < 0.10. Omega and alpha coefficients were calculated. The explanatory model was tested using Structural Equation Modeling. Analyses were performed with SPSS 27 and R (R Studio interface), employing the lavaan package version 0.6–17, psych version 2.4.1, semTools version 0.5–6, and MVN version 5.9. Results The perspective-taking dimension of empathy was significantly predicted by the ecological dimension (positively) and the adaptation dimension (negatively) of resilience. The other dimensions did not show predictive capacity. Conclusion This study concludes that resilience partially predicts empathy in the population studied. Therefore, resilience could be considered an attribute to incorporate into teaching-learning processes aimed at increasing empathy levels. The scope and implications of these findings are discussed.

Frontiers in EducationVol. 10
Universidad Andrés Bello (CL), Universidad Santiago de Cali (CO), Universidad Católica Santo Toribio de Mogrovejo (PE)
Universidad Santiago de Cali
Openalex Percentile: Top 14%
Empathy and Medical Education
1.47
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